Real Time AI-Based Pipeline Inspection using Drone for Oil and Gas Industries in Bahrain

2020 ◽  
Author(s):  
Aysha Alharam ◽  
Ebrahim Almansoori ◽  
Wael Elmadeny ◽  
Hasan Alnoiami
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Pipeline Inspection

scholarly journals New Monitoring Architectures for underwater oil/Gas Pipeline using Hyper sensors

10.29007/c84d ◽  
2020 ◽  
Author(s):  
Huda Aldosari ◽  
Raafat Elfouly ◽  
Reda Ammar ◽  
Mohammad Alsulami
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Data Transfer ◽  
Gas Pipeline ◽  
Wireless Sensor ◽  
Inspection System ◽  
Pipeline Inspection ◽  
Oil And Gas Pipelines ◽  
Main Station ◽  
Oil Gas

In this paper we propose new real time architectures for monitoring underwater oil and gas pipelines by using underwater wireless sensor network (UWSN). New monitoring architectures for underwater oil/gas pipeline inspection system combine a real time UWSN with nondestructive In Line Inspection (ILI) technology. These architecture will help in reducing or detecting the pipeline’s defects such as cracks, corrosions, welds, pipeline’s wall thickness ...etc by improving data transfer from the pipeline to the processor to extract useful information and deliver it to the onshore main station. Hence, decreasing delays in default detection.

scholarly journals Development of Real-Time Time Gated Digital (TGD) OFDR Method and Its Performance Verification

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4865
Author(s):  
Kinzo Kishida ◽  
Artur Guzik ◽  
Ken’ichi Nishiguchi ◽  
Che-Hsien Li ◽  
Daiji Azuma ◽  
...  
Keyword(s):  
Real Time ◽  
Optical Fibers ◽  
High Speed ◽  
Oil And Gas ◽  
Scattered Light ◽  
Oil And Gas Industry ◽  
High Signal ◽  
Chirp Pulse ◽  
Sound Waves ◽  
Industry Applications

Distributed acoustic sensing (DAS) in optical fibers detect dynamic strains or sound waves by measuring the phase or amplitude changes of the scattered light. This contrasts with other distributed (and more conventional) methods, such as distributed temperature (DTS) or strain (DSS), which measure quasi-static physical quantities, such as intensity spectrum of the scattered light. DAS is attracting considerable attention as it complements the conventional distributed measurements. To implement DAS in commercial applications, it is necessary to ensure a sufficiently high signal-noise ratio (SNR) for scattered light detection, suppress its deterioration along the sensing fiber, achieve lower noise floor for weak signals and, moreover, perform high-speed processing within milliseconds (or sometimes even less). In this paper, we present a new, real-time DAS, realized by using the time gated digital-optical frequency domain reflectometry (TGD-OFDR) method, in which the chirp pulse is divided into overlapping bands and assembled after digital decoding. The developed prototype NBX-S4000 generates a chirp signal with a pulse duration of 2 μs and uses a frequency sweep of 100 MHz at a repeating frequency of up to 5 kHz. It allows one to detect sound waves at an 80 km fiber distance range with spatial resolution better than a theoretically calculated value of 2.8 m in real time. The developed prototype was tested in the field in various applications, from earthquake detection and submarine cable sensing to oil and gas industry applications. All obtained results confirmed effectiveness of the method and performance, surpassing, in conventional SM fiber, other commercially available interrogators.

Proxy Model for Real-Time Estimation of Cool Down Time of Subsea Production System to Prevent Hydrates Formation

2021 ◽  
Author(s):  
Joseph Rizzo Cascio ◽  
Antonio Da Silva ◽  
Martino Ghetti ◽  
Martino Corti ◽  
Marco Montini
Keyword(s):  
Real Time ◽  
Production System ◽  
Field Data ◽  
Oil And Gas ◽  
Time Estimation ◽  
Integrated Approach ◽  
Proxy Model ◽  
Real Time Estimation ◽  
Subsea Production System ◽  
Formation Of Hydrates

Abstract Objectives/Scope The benefits of real-time estimation of the cool down time of Subsea Production System (SPS) to prevent formation of hydrates are shown on a real oil and gas facility. The innovative tool developed is based on an integrated approach, which embeds a proxy model of SPS and hydrate curves, exploiting real-time field data from the Eni Digital Oil Field (eDOF, an OSIsoft PI based application developed and managed by Eni) to continuously estimate the cool down time before hydrates are formed during the shutdown. Methods, Procedures, Process The Asset value optimization and the Asset integrity of hydrocarbon production systems are complex and multi-disciplinary tasks in the oil and gas industry, due to the high number of variables and their synergy. An accurate physical model of SPS is built and, then, used to develop a proxy model, which integrates hydrate curves at different MeOH concentration, being able to estimate in real time the cool down time of SPS during the shutdown exploiting data from subsea transmitters made available by eDOF in order to prevent formation of hydrates. The tool is also integrated with a user-friendly interface, making all relevant information readily available to the operators on field. Results, Observations, Conclusions The integrated approach provides a continues estimation of cool down time based on real time field data (eDOF) in order to prevent formation of hydrates and activate preservation actions. An accurate physical model of SPS is built on a real business case using Olga software and cool down curves simulated considering different operating shutdown scenarios. Hydrate curves of the considered production fluid are also simulated at different MeOH concentration using PVTsim NOVA software. Off-line simulated curves are then implemented as numerical tables combined with eDOF data by an Eni developed fast executing proxy model to produce estimated cool down time before hydrates are formed. A graphic representation of SPS behavior and its cool down time estimation during shutdown are displayed and ready to use by the operators on field in support of the operations, saving cost and time. Novel/Additive Information The benefits of real time estimation of the cool down time of SPS to prevent hydrates formation are shown in terms of saving of time and cost during the shutdown operations on a real case application. This integrated approach allows to rely on a continue, automatic and acceptably accurate estimate of the available time before hydrates are formed in SPS, including the possibility to be further developed for cases where subsea transmitters are not available or extended to other flow assurance issues.

A Novel Corrosion Monitoring and Prediction System Utilizing Advanced Artificial Intelligence

2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Waleed Dokhon ◽  
Fahmi Aulia ◽  
Mohanad Fahmi
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Salt Water ◽  
Oil And Gas Industry ◽  
Training Dataset ◽  
Metal Loss ◽  
Corrosion Monitoring ◽  
Prediction System ◽  
Well Performance ◽  
Data Driven Approach

Abstract Corrosion in pipes is a major challenge for the oil and gas industry as the metal loss of the pipe, as well as solid buildup in the pipe, may lead to an impediment of flow assurance or may lead to hindering well performance. Therefore, managing well integrity by stringent monitoring and predicting corrosion of the well is quintessential for maximizing the productive life of the wells and minimizing the risk of well control issues, which subsequently minimizing cost related to corrosion log allocation and workovers. We present a novel supervised learning method for a corrosion monitoring and prediction system in real time. The system analyzes in real time various parameters of major causes of corrosion such as salt water, hydrogen sulfide, CO2, well age, fluid rate, metal losses, and other parameters. The data are preprocessed with a filter to remove outliers and inconsistencies in the data. The filter cross-correlates the various parameters to determine the input weights for the deep learning classification techniques. The wells are classified in terms of their need for a workover, then by the framework based on the data, utilizing a two-dimensional segmentation approach for the severity as well as risk for each well. The framework was trialed on a probabilistically determined large dataset of a group of wells with an assumed metal loss. The framework was first trained on the training dataset, and then subsequently evaluated on a different test well set. The training results were robust with a strong ability to estimate metal losses and corrosion classification. Segmentation on the test wells outlined strong segmentation capabilities, while facing challenges in the segmentation when the quantified risk for a well is medium. The novel framework presents a data-driven approach to the fast and efficient characterization of wells as potential candidates for corrosion logs and workover. The framework can be easily expanded with new well data for improving classification.

Near-Real-Time Seismic Monitoring for Pipelines

2018 ◽  
Author(s):  
Martin Zaleski ◽  
Gerald Ferris ◽  
Alex Baumgard
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Earthquake Hazard ◽  
Lateral Spreading ◽  
Soil Liquefaction ◽  
Gas Pipelines ◽  
Hazard Management ◽  
Earthquake Probability ◽  
Oil And Gas Pipelines ◽  
Map Data

Earthquake hazard management for oil and gas pipelines should include both preparedness and response. The typical approach for management of seismic hazards for pipelines is to determine where large ground motions are frequently expected, and apply mitigation to those pipeline segments. The approach presented in this paper supplements the typical approach but focuses on what to do, and where to do it, just after an earthquake happens. In other words, we ask and answer: “Is the earthquake we just had important?”, “What pipeline is and what sites might it be important for?”, and “What should we do?” In general, modern, high-pressure oil and gas pipelines resist the direct effects of strong shaking, but are vulnerable to large co-seismic differential permanent ground displacement (PGD) produced by surface fault rupture, landslides, soil liquefaction, or lateral spreading. The approach used in this paper employs empirical relationships between earthquake magnitude, distance, and the occurrence of PGD, derived from co-seismic PGD case-history data, to prioritize affected pipeline segments for detailed site-specific hazard assessments, pre-event resiliency upgrades, and post-event response. To help pipeline operators prepare for earthquakes, pipeline networks are mapped with respect to earthquake probability and co-seismic PGD susceptibility. Geological and terrain analyses identify pipeline segments that cross PGD-susceptible ground. Probabilistic seismic models and deterministic scenarios are considered in estimating the frequency of sufficiently large and close causative earthquakes. Pipeline segments are prioritized where strong earthquakes are frequent and ground is susceptible to co-seismic PGD. These may be short-listed for mitigation that either reduces the pipeline’s vulnerability to damage or limits failure consequences. When an earthquake occurs, pipeline segments with credible PGD potential are highlighted within minutes of an earthquake’s occurrence. These assessments occur in near-real-time as part of an online geohazard management database. The system collects magnitude and location data from online earthquake data feeds and intersects them against pipeline network and terrain hazard map data. Pipeline operators can quickly mobilize inspection and response resources to a focused area of concern.

scholarly journals IMPACT OF GAS LIFT INJECTION RATE ON OIL PRODUCTION RATE

2021 ◽  
pp. 76-94
Author(s):  
Dr. Mohamed A. GH. Abdalsadig
Keyword(s):  
Real Time ◽  
Energy Demand ◽  
Oil And Gas ◽  
Injection Pressure ◽  
Production Operation ◽  
Well Performance ◽  
Time Data ◽  
Daily Work ◽  
Wellhead Pressure ◽  
Gas Lift

As worldwide energy demand continues to grow, oil and gas fields have spent hundreds of billions of dollars to build the substructures of smart fields. Management of smart fields requires integrating knowledge and methods in order to automatically and autonomously handle a great frequency of real-time information streams gathered from those wells. Furthermore, oil businesses movement towards enhancing everyday production skills to meet global energy demands signifies the importance of adapting to the latest smart tools that assist them in running their daily work. A laboratory experiment was carried out to evaluate gas lift wells performance under realistic operations in determining reservoir pressure, production operation point, injection gas pressure, port size, and the influence of injection pressure on well performance. Lab VIEW software was used to determine gas passage through the Smart Gas Lift valve (SGL) for the real-time data gathering. The results showed that the wellhead pressure has a large influence on the gas lift performance and showed that the utilized smart gas lift valve can be used to enhanced gas Lift performance by regulating gas injection from down hole.

scholarly journals Dynamic Efficiency Analysis of an Off-Shore Hydrocyclone System, Subjected to a Conventional PID- and Robust-Control-Solution

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2379 ◽  
Author(s):  
Petar Durdevic ◽  
Zhenyu Yang
Keyword(s):  
Robust Control ◽  
Real Time ◽  
Oil And Gas ◽  
Control Structure ◽  
Control Strategies ◽  
Direct Method ◽  
Water Concentration ◽  
Current Feedback ◽  
Oil Concentration ◽  
Offshore Oil And Gas

There has been a continued increase in the load on the current offshore oil and gas de-oiling systems that generally consist of three-phase gravity separators and de-oiling hydrocyclones. Current feedback control of the de-oiling systems is not done based on de-oiling efficiency, mainly due to lack of real-time monitoring of oil-in-water concentration, and instead relies on an indirect method using pressure drop ratio control. This study utilizes a direct method where a real-time fluorescence-based instrument was used to measure the transient efficiency of a hydrocyclone combined with an upstream gravity separator. Two control strategies, a conventional PID control structure and an H ∞ robust control structure, both using conventional feedback signals were implemented, and their efficiency was tested during severely fluctuating flow rates. The results show that the direct method can measure the system’s efficiency in real time. It was found that the efficiency of the system can be misleading, as fluctuations in the feed flow affect the inlet concentration more than the outlet oil concentration, which can lead to a discharge of large oil quantities into the ocean.

A Seismic Alert System for Oil & Gas Offshore Fields

2021 ◽  
Author(s):  
Pamela Poggi ◽  
Emilia Fiorini ◽  
Daniela Tonoli ◽  
Francesca Ioele ◽  
Eric John Parker ◽  
...  
Keyword(s):  
Real Time ◽  
Ground Motion ◽  
Oil And Gas ◽  
Focal Depth ◽  
Threshold Values ◽  
Alert System ◽  
Ground Acceleration ◽  
Gas Field ◽  
Expected Values ◽  
Earthquake Data

Abstract Objectives/Scope This paper presents an innovative web tool developed for the seismic monitoring of critical infrastructure. As an example, we describe an application for the ENI offshore facilities, Jangkrik and Merakes Fields Development, offshore Indonesia. Methods, Procedures, Process The system monitors reported seismic activity in a project area, and issues warnings when earthquakes detected may have directly or indirectly impacted facilities. Notifications allow the owner to optimize decisions regarding post-earthquake asset surveys and maintenance, avoiding the need for inspections in areas not significantly affected. A system of email alerts and a web based GIS platform provide the end-user with a tool to control its own assets. Results, Observations, Conclusions The purpose of the tool is to indirectly monitor earthquakes in an area and identify those which may have damaged the Oil and Gas facilities of interest. This identification requires accurate near real-time earthquake data such as date, time, location, magnitude, and focal depth. To this end, the system retrieves earthquake data from a qualified set of public seismic agencies. The system computes the expected values of shaking at the specific offshore facilities (platforms, subsea structures, pipelines, etc.). Calculations are based on sets of Ground Motion Prediction Equations (GMPEs) selected to match the seismotectonic environment. The expected values of seismic acceleration generated by an earthquake are compared with threshold values and a warning message is issued to the facilities supervisors when the ground acceleration exceeds design values. Threshold values related to secondary seismic effects (e.g., seismically induced landslides, debris flow) which could affect facilities integrity are also considered in the alert system. Threshold values are defined considering project seismic and geohazard documents, to summarize strong ground motion parameters that could potentially trigger damaging seismic geohazards, and project design documents to collect all data about seismic design of the assets. Monitoring intervals are defined based on the documentation screening. Several alarm levels are selected, based on the potential severity of earthquake effects. The more severe levels of ground motion, with high damage potential, can trigger recommendation for inspection. Novel/Additive Information Asset integrity and safety are key drivers in the offshore petroleum industry. Safety performance with respect to earthquakes is a fundamental issue in all seismic prone areas. The seismic alert system presented highlights, in near real time, earthquakes that are potentially critical for structures in an Oil and Gas field. This allows the owners to make quick decisions and plan necessary intervention regarding assets affected directly or indirectly by earthquakes. Exploiting the wide background of knowledge in engineering and geoscience and the modern availability of global earthquake data, the tool can provide useful assistance in managing asset integrity, regardless of the availability of local seismic networks or strong motion stations.

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